Electronic Theses and Dissertations (Masters)

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    Optically stimulated luminescence dating of Kalundu and Urewe tradition ceramics
    (University of the Witwatersrand, Johannesburg, 2024-03) Haupt, Rachel Xenia; Schoeman, Maria; Evans, Mary
    Optically stimulated luminescence (OSL) dating is a method of providing the direct age of artefacts. While radiocarbon and seriation dating provide indispensable insight into archaeological sites, the direct dating of artefacts is beneficial in entangled contexts. The Lydenburg Heads Site is significant to the beginning of the Early Farming Communities (EFCs) sequence within the Mpumalanga province. The site has been occupied multiple times, as can be seen from the presence of the two major ceramic traditions of the age, Urewe and Kalundu. The site was originally excavated and analysed by Evers (1982) in the 1970s, with a reanalysis of the ceramic assemblage by Whitelaw (1996) and organic residue analysis on the ceramics by Becher (2021). The use of OSL dating on twelve ceramic sherds allowed for new insights into the chronological intricacies within the study site. To determine the age of the ceramics, the OSL quartz dating technique was used. The adjustments to the technique involved the use of a less destructive means of sample extraction. A slightly altered version of the standard means of sample extraction was used to create a comparison and allow the dating of the ceramics to be reliable. The minimal destruction technique (MET) combined with the bulk sampling proved useful to the dating of the ceramics. The use of previously excavated ceramics meant that some aspects of age determination required estimation and analysis. The major obstacles from such were the water content, the depth of burial, and the lack of in situ soil samples. In light of the elements of ambiguity for the site, the OSL dating considered these variations and how they affected the age. The Urewe tradition ceramics were determined to be in 6th and 8th century AD. The finding creates the alignment with the range of the radiocarbon ages done within previous work and the assumptions made by Evers (1982) and Whitelaw (1996). The Kalundu tradition ceramics ages were determined to be between the 7th and 10th century AD, conflicting with previous assumptions on the occupation. The result is the possibility the ceramic assemblages could be considered to be contemporaneous. The work in this thesis has, in part, been presented at the Luminescence and Electron Spin Resonance Dating conference in Copenhagen (LED2023) and at the Association of Southern African Professional Archaeologists 2024 Biennial Meeting (ASAPA 2024).
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    The Influence of Climate Change on the Speed of Movement of Tropical Cyclones in the South Indian Ocean
    (University of the Witwatersrand, Johannesburg, 2024-07) Mahomed, Aaliyah; Fitchett, Jennifer
    Recent studies on the speed of movement of tropical cyclones indicate that anthropogenic warming has resulted in a 10% global decrease of tropical cyclone translation speeds over the period 1949-2016. The recent increase in high intensity storms could severely impact Southern Hemisphere regions which are considerably more vulnerable than their Northern Hemisphere counterparts. High intensity storms occurring at a lower speed would worsen the impacts of tropical cyclones resulting in prolonged periods of flooding, storm surges, and winds. This would subsequently lead to a loss of lives, economic loss and infrastructural and agricultural damage. However, studies have challenged this slowdown, suggesting that the transition to the geo-stationary era, introduces heterogeneity to tropical cyclone data. Additionally, imprecise estimates of tropical cyclone frequency influences the average speed of tropical cyclones, thereby impacting trend analysis. Using tropical cyclone data from National Oceanic and Atmospheric Administration (NOAA) International Best Track Archive for Climate Stewardship (IBTrACS), this study explores the current translation speed debate for the South Indian Ocean, over the period 1991-2021. The results of this study indicate that the translation speed of tropical cyclones has increased at a rate of 0.06km/h/yr over the 30-year period (r = 0.06 p = 0.19). Whilst the translation speed debate remains at an aggregated global scale, a comprehensive understanding of the influence of climate change on tropical cyclones is crucial for generating forecasts as this enables vulnerable regions to plan and adjust to evolving tropical cyclones.
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    GIS-Based Location-Allocation Modelling of School Accessibility in the Bojanala Platinum District Municipality, South Africa
    (University of the Witwatersrand, Johannesburg, 2024-09) Molefe, Kebarileng Christinah; Atif, Iqra
    School accessibility modelling performs a crucial part in guaranteeing that educational institutions are physically and practically reachable by every student, irrespective of their abilities, disabilities, or socioeconomic status. Neglecting school accessibility perpetuates inequality, reinforces negative stereotypes, and isolates affected students. Therefore, the principal goal of this research was to evaluate the distribution of schools across the Bojanala Platinum District Municipality, focusing on their accessibility to local communities. The study employed an integrated approach, combining geostatistical techniques, location-allocation modelling, and multicriteria decision analysis. By considering both quantitative data and spatial relationships, these methodologies contributed to robust decision-making and informed policy recommendations. The study utilized population data and school-related information sourced from the Department of Education and the HUMDATA websites, both dated to the year 2020. The study examined the distribution of schools in the Bojanala Platinum District Municipality. It was discovered that the schools were clustered, with a concentration in the Rustenburg local municipality, followed by Madibeng. However, a significant inequality in school access was evident. Secondary school students faced the greatest vulnerability, as most accessible schools primarily served primary students. To address this, potential school sites were proposed across the district. The study emphasizes the need for effective interventions by educational administrators and policymakers to eliminate this inequality. This study recommends the establishment of new schools in underserved regions, strategically enhance existing schools, and maximize school accessibility for all residents. Adequate school provision promotes equity, reduces travel burdens, and strengthens community bonds.
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    Detecting Disease in Citrus Trees using Multispectral UAV Data and Deep Learning Algorithm
    (University of the Witwatersrand, Johannesburg, 2024-06) Woolfson, Logan Stefan; Adam, Elhadi
    There is a high prevalence, in South Africa, of fruit tree related diseases infesting lemon trees, subsequently affecting overall crop yield and quality. Ultimately, the income for the farmers is significantly diminished and limits the supply of nutritional food crops for the South African population, who already suffer from a high incidence of malnutrition. Currently, there are various methods utilized to detect diseases in fruit trees, however they pose limitations in terms of efficiency and accuracy. By employing the use of drones and machine learning methods, fruit tree diseases could be detected at an earlier stage of development and with a much higher level of accuracy. Consequently, the chances of remedying the trees before the disease spreads is greatly improved, and the supply of nutritious fruit within South Africa is increased. This research report’s aim is to investigate the effectiveness of a deep learning algorithm for detecting and classifying diseases in lemon orchards using multispectral drone imagery. This entails assessing the performance of a pretrained ResNet-101 model, fine-tuned with additional sample images, in accurately identifying and classifying diseased lemon trees, specifically those affected by Phytophthora root rot. The methodology involves the utilization of a pretrained ResNet-101 model, a deep learning architecture, and the retraining of its layers with an augmented dataset from multispectral aerial drone images of a lemon orchard. The model is fine-tuned to enhance its ability to discern subtle spectral variations indicative of disease presence. The selection of ResNet-101 is grounded in its proven success in image recognition tasks and transfer learning capabilities. The results obtained demonstrated an impressive accuracy of 80%. The deep learning algorithm exhibited notable performance in distinguishing root rot-affected lemon trees from their healthy counterparts. The findings indicate the promise of utilizing advanced deep learning methods for timely and effective disease detection in agricultural farmlands, facilitating orchard management.
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    Lessons for South Africa’s proposed social security retirement reforms from the experience of other sub-Saharan African countries
    (University of the Witwatersrand, Johannesburg, 2024) Walker, Stephen
    The South African government intends reforming its current social security system, including retirement benefits. Views on how this should be done vary, even within government. Proposals often take the experience of other countries into consideration but there is limited literature on the experience of other sub-Saharan African countries. The region is experiencing demographic change, especially reduced infant mortality, reduced fertility and increasing old age longevity. Here South Africa is advanced relative to other countries in the region, despite the high unemployment levels. South Africa’s informal sector is large relative to developed countries, but smaller than elsewhere in Sub-Saharan Africa. Countries in the region have tried several approaches when introducing reform. Level A non- contributory pensions in South Africa are advanced, relative to most countries in the region. Most other countries have mandatory, contributory, government-run level B funds, the closest equivalent in South Africa is the Unemployment Insurance Fund. DB level B schemes are the norm. However, many countries are experiencing strain on the financial sustainability of these schemes and a number of countries have had to increase scheme contributions or reduce benefits. Occupational retirement funds in South Africa are well established and have experienced significant reforms recently. South Africa’s level C2 occupational retirement fund coverage is not mandated by government but is high relative to other countries in the region, even those with compulsory coverage under level C1. South Africa is still relatively new to introducing contributory pensions for informal sector workers. Other countries have tried various approaches under both levels D1 and D2 without finding a perfect solution. The research shows that maximising coverage requires all pension types. Pension reform is an iterative process, there is no perfect solution and phasing-in change is best. Government should make decisions on what incremental improvements can be made and start implementing these. The sequencing of reforms is important, what happens at each level of pension provision will influence what can and should be done at the next level. South Africa should move towards universalisation of non-contributory pensions but needs to do so in a cost-effective manner. The experience in other countries in the region should be considered when setting goals for coverage of informal sector workers by a level D1 or D2 contributory scheme. Compulsory contributory pensions should be introduced for formal sector workers, shifting from a level C2 to a level C1 approach. Expanding the Unemployment Insurance Fund to cater for retirement benefits as opposed to creating a new level B national fund should be explored.